Convective SIGMETs: A Climatological Retrospective and Thoughts for Future Enhancements

Several years ago, a climatology of Convective SIGMETs (CSIGs) was conducted. Herein, we revisit those results with more recent data and consider how this retrospective can be used to advance the next generation of CSIG production. As has been previously shown, there are pronounced seasonal variations in CSIGs, with winter months having the lowest and summer/early fall having the highest frequencies. One of the more intriguing results of this study and the previous work is that there is a pronounced interannual variability of CSIGs that appears to be related to large-scale circulation patterns, such as the Madden-Julian Oscillation. At the time of this writing, this is still being investigated, but it may be possible to exploit this connection for seasonal route planning to mitigate the effects of convection on flight delays.

An assessment of the different forms of weather that result in CSIGs is conducted. Most CSIGs are issued for sea-breeze-induced convection along the Gulf Coast, orographically-induced convection associated with the North American Monsoon, and mesoscale convective systems in the Great Plains. CSIGs are found to have a rather wide range of intensities and, hence, constitute different degrees of threats. This has two side effects. First, it opens the door to a certain degree of forecaster subjectivity as they attempt to discern whether the threat raises itself to the level of a CSIG. Indeed, there is inconsistency on whether CSIGs are issued for lower-end threats. Second, it leads one to question: Could different intensity levels be assigned to CSIGs and, if so, would that provide enhanced safety in the National Air Space? Another open question raised by this study is related to the movement of convection relative to the polygons. By convention, polygons are drawn as a snapshot to represent the hazard at the time of issuance. This often results in rapidly-moving storms moving outside the boundaries of the polygons before subsequent updates. This is most common with comparatively violent MCSs/QLCSs in the Great Plains during the warm season. The current methodology to deal with this is to provide motion vectors, which are based on the recent history of the storm and, hence, cannot account for changes in storm morphology or for convective initiation after issuance. Perhaps the next-generation of CSIGs should take advantage of innovation with improved numerical weather prediction at short ranges to provide probabilistic guidance of CSIG activity for the valid period of the CSIG. A prototype showing how this may be efficiently provided to CSIG production meteorologists and end users will be presented.